Developer Reference

Intel® oneAPI Math Kernel Library LAPACK Examples

ID 766877
Date 3/31/2023
Public

A newer version of this document is available. Customers should click here to go to the newest version.

Document Table of Contents

LAPACK Examples

Routine Description Examples
?geev Computes the eigenvalues and, optionally, the left and/or right eigenvectors of a general matrix.

cgeev

dgeev

sgeev

zgeev

?gels Uses QR or LQ factorization to solve an overdetermined or underdetermined linear system with a full rank matrix.

cgels

dgels

sgels

zgels

?gelsd Computes the minimum norm solution to a linear least squares problem using the singular value decomposition of A and a divide and conquer method.

cgelsd

dgelsd

sgelsd

zgelsd

?gesdd Computes the singular value decomposition of a general rectangular matrix using a divide and conquer algorithm.

cgesdd

dgesdd

sgesdd

zgesdd

?gesv Computes the solution to the system of linear equations with a square matrix A and multiple right-hand sides.

cgesv

dgesv

sgesv

zgesv

?gesvd Computes the singular value decomposition of a general rectangular matrix.

cgesvd

dgesvd

sgesvd

zgesvd

?heev Computes all the eigenvalues and, optionally, the eigenvectors of a Hermitian matrix.

cheev

zheev

?heevd Computes all the eigenvalues and, optionally, all the eigenvectors of a complex Hermitian matrix using a divide and conquer algorithm.

cheevd

zheevd

?heevr Computes the selected eigenvalues and, optionally, the eigenvectors of a Hermitian matrix using the Relatively Robust Representations.

cheevr

zheevr

?heevx Computes the selected eigenvalues and, optionally, the eigenvectors of a Hermitian matrix.

cheevx

zheevx

?hesv Computes the solution to the system of linear equations with a Hermitian matrix A and multiple right-hand sides.

chesv

zhesv

?posv Computes the solution to the system of linear equations with a symmetric or Hermitian positive definite matrix A and multiple right-hand sides.

cposv

dposv

sposv

zposv

?syev Computes all the eigenvalues and, optionally, the eigenvectors of a real symmetric matrix.

dsyev

ssyev

?syevd Computes all the eigenvalues and, optionally, all the eigenvectors of a real symmetric matrix using a divide and conquer algorithm.

dsyevd

ssyevd

?syevr Computes the selected eigenvalues and, optionally, the eigenvectors of a real symmetric matrix using the Relatively Robust Representations.

dsyevr

ssyevr

?syevx Computes the selected eigenvalues and, optionally, the eigenvectors of a symmetric matrix.

dsyevx

ssyevx

?sysv Computes the solution to the system of linear equations with a real or complex symmetric matrix A and multiple right-hand sides.

csysv

dsysv

ssysv

zsysv